How would you characterize an effect size of d = .27? Negligible Small Medium Large What...

How would you characterize an effect size of d = .27?

Negligible

Small

Medium

Large

What level of measurement is the ranking of baseball teams in the ASUN conference?

		Nominal
		Ordinal
		Interval
		Ratio

What are the three measures of central tendency? List the three measures of central tendency and provide an example of the type of data or distribution in which it is best to use each.

What are the two types of errors that can be made in statistical inference? Define each type of error.

Expert Solution

1. Here , d = 0.27

As the effect size is less than 0.5 and greater than 0.2 we will say this is a Small effect size.

2. The ranking of baseball teams in the the ASUN conference is a Measurement of Ordinal scale . Because in the ranking there is ordering within the variables.

3. Mean , median and mode are the three measures of Central tendency .

Mean - mean is the best measure of Central tendency as it includes all the data points. Mean can be used all the times but if the data is skewed or there are outliers in the data then mean shows some inaccurate Measures. So mean is best when the data is symmetric.

Median - median is the middle most value of the data set. So when the data is highly skewed or there is too many outliers median should be used then because median doesn't depend on all the data points. Because in this case median is not affected by the outliers .

Mode - mode should be used in case of categorical variables. Whenever we want to know Which category has the most frequency then mode should be used.

4. In statistical inference there are two types of errors. One is Type I error and another is type II error.

Type I error - if we reject the null hypothesis in our test , but in real the null hypothesis is not false that means if we reject the null hypothesis when it's true it is call Type I error.

Type II error- if we fail to reject the null hypothesis in our test but in real life the null hypothesis is not true , that means if we fail to reject the null hypothesis when it's false, it is called type II error .

orchestra answered 2 years ago

. How do you determine if an effect is small, medium, or large?

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